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Editorial Team
Asked: May 13, 20262026-05-13T20:19:16+00:00 2026-05-13T20:19:16+00:00

I have built software that I deploy on Windows 2003 server. The software runs

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I have built software that I deploy on Windows 2003 server. The software runs as a service continuously and it’s the only application on the Windows box of importance to me. Part of the time, it’s retrieving data from the Internet, and part of the time it’s doing some computations on that data. It’s multi-threaded — I use thread pools of roughly 4-20 threads.

I won’t bore you with all those details, but suffice it to say that as I enable more threads in the pool, more concurrent work occurs, and CPU use rises. (as does demand for other resources, like bandwidth, although that’s of no concern to me — I have plenty)

My question is this: should I simply try to max out the CPU to get the best bang for my buck? Intuitively, I don’t think it makes sense to run at 100% CPU; even 95% CPU seems high, almost like I’m not giving the OS much space to do what it needs to do. I don’t know the right way to identify best balance. I guessing I could measure and measure and probably find that the best throughput is achived at a CPU avg utilization of 90% or 91%, etc. but…

I’m just wondering if there’s a good rule of thumb about this??? I don’t want to assume that my testing will take into account all kinds of variations of workloads. I’d rather play it a bit safe, but not too safe (or else I’m underusing my hardware).

What do you recommend? What is a smart, performance minded rule of utilization for a multi-threaded, mixed load (some I/O, some CPU) application on Windows?

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  1. Editorial Team
    Editorial Team
    2026-05-13T20:19:16+00:00Added an answer on May 13, 2026 at 8:19 pm

    Yep, I’d suggest 100% is thrashing so wouldn’t want to see processes running like that all the time. I’ve always aimed for 80% to get a balance between utilization and room for spikes / ad-hoc processes.

    An approach i’ve used in the past is to crank up the pool size slowly and measure the impact (both on CPU and on other constraints such as IO), you never know, you might find that suddenly IO becomes the bottleneck.

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